With applications ranging from diagnostic procedures to radiation therapy, the importance of high-performance medical imaging is immeasurable. As such, new advanced medical imaging technologies continue to be developed. Digital medical imaging techniques represent the future of medical imaging. Digital imaging systems produce far more accurate and detailed images of an object than conventional film-based imaging systems, and also allow further enhancements of the images to be made once an object is scanned.
During the display processing of images from digital radiographic imaging systems, the image noise at highly attenuated regions in the images becomes more noticeable, and can therefore decrease the perceived quality of the final images. This perceived image degradation is mainly due to the contrast enhancement that occurs in the highly attenuated regions of the image. Currently, noise reduction techniques based on image properties alone can greatly improve the perceived quality of highly attenuated regions of such images. However, that comes at the cost of having decreased contrast at lowly attenuated regions in the images, such as the lung parenchyma. Since existing systems and methods for reducing noise in digital x-ray images have such drawbacks, it would be desirable to have systems and methods for improving the displayed image quality of digital x-ray images that can reduce noise at highly attenuated regions without affecting the image contrast at relatively lowly attenuated regions. It would also be desirable to have such systems and methods that take the detected signal properties into account in a noise reduction framework, where the noise reduction framework is adaptive to the detected signal.